tests/testthat/test_softmax.R
In LudvigOlsen/cvms: Cross-Validation for Model Selection
library(cvms)
context("softmax()")
test_that("softmax_vector() works", {
logits <- c(2, 57, 76, 23, 65, 0.3, 65.3)
exp_logits <- exp(logits)
sum_exp_logits <- sum(exp_logits)
softmaxed <- exp_logits/sum_exp_logits
expect_equal(softmax_vector(logits), softmaxed)
expect_equal(softmax_vector(2, 57, 76, 23, 65, 0.3, 65.3), softmaxed)
expect_equal(sum(softmax_vector(logits)), 1)
expect_equal(sum(softmax_vector(-logits)), 1)
## Testing 'softmax_vector(logits)' ####
## Initially generated by xpectr
# Assigning output
output_12505 <- softmax_vector(logits)
# Testing class
expect_equal(
class(output_12505),
"numeric",
fixed = TRUE)
# Testing type
expect_type(
output_12505,
type = "double")
# Testing values
expect_equal(
output_12505,
c(7.28100438257926e-33, 5.60257652385053e-09, 0.999960749299178,
9.60230314258677e-24, 1.67010452367847e-05, 1.33011953925298e-33,
2.25440530085991e-05),
tolerance = 1e-4)
# Testing names
expect_equal(
names(output_12505),
NULL,
fixed = TRUE)
# Testing length
expect_equal(
length(output_12505),
7L)
# Testing sum of element lengths
expect_equal(
sum(xpectr::element_lengths(output_12505)),
7L)
## Finished testing 'softmax_vector(logits)' ####
})
test_that("softmax() works", {
df <- data.frame(
"l1" = c(2, 57, 76, 23, 65, 0.3, 65.3),
"l2" = c(5, 2, 45,-10,-42, 23, 56.2),
"l3" = c(42, 12.6, 21, 43.2, 1, 0, 98),
"c1" = factor(c("a", "b", "c", "d", "e", "f", "g"),
levels = c("a", "b", "c", "d", "e", "f", "g"))
)
vector_softmax <- function(...){
exp_logits <- exp(c(...))
sum_exp_logits <- sum(exp_logits)
exp_logits/sum_exp_logits
}
df_colwise_softmaxed <- df %>%
dplyr::mutate(l1 = vector_softmax(l1),
l2 = vector_softmax(l2),
l3 = vector_softmax(l3))
expect_equal(as.data.frame(softmax(df, cols = c("l1", "l2", "l3"), axis = "c"), stringsAsFactors=TRUE),
as.data.frame(df_colwise_softmaxed), stringsAsFactors=TRUE)
df_rowwise_softmaxed <- plyr::ldply(seq_len(nrow(df)), function(r){
vector_softmax(unlist(df[r,c("l1","l2","l3")], recursive = TRUE, use.names = TRUE))
}) %>% dplyr::as_tibble() %>%
dplyr::mutate(c1 = df$c1)
expect_equal(as.data.frame(softmax(df, cols = c("l1", "l2", "l3"), axis = "r"), stringsAsFactors=TRUE),
as.data.frame(df_rowwise_softmaxed), stringsAsFactors=TRUE)
## Test with gxs_function
# xpectr::gxs_function(fn = softmax,
# args_values = list(
# "data" = list(df, NA, 1),
# "cols" = list(c("l1", "l2", "l3"),
# c(1, 2, 3),
# 4, NA, "l4"),
# "axis" = list("r", "c", "x", NA)
# ), indentation = 2,
# tolerance = "1e-10",
# round_to_tolerance = FALSE)
#
## Testing 'softmax' ####
## Initially generated by xpectr
# Testing different combinations of argument values
# Testing softmax(data = NA, cols = c("l1", "l2", "l3"),...
# Testing side effects
expect_error(
xpectr::strip_msg(softmax(data = NA, cols = c("l1", "l2", "l3"), axis = "r")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'data': Must be of type 'd",
"ata.frame', not 'logical'.")),
fixed = TRUE)
# Testing softmax(data = 1, cols = c("l1", "l2", "l3"), ...
# Testing side effects
expect_error(
xpectr::strip_msg(softmax(data = 1, cols = c("l1", "l2", "l3"), axis = "r")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'data': Must be of type 'd",
"ata.frame', not 'double'.")),
fixed = TRUE)
# Testing softmax(data = df, cols = c(1, 2, 3), axis = "r")
# Assigning output
output_12030 <- softmax(data = df, cols = c(1, 2, 3), axis = "r")
# Testing class
expect_equal(
class(output_12030),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
output_12030[["l1"]],
c(4.24835425529159e-18, 1, 0.999999999999972, 1.68752985466077e-09,
1, 1.38520885997973e-10, 6.28883849646162e-15),
tolerance = 1e-10)
expect_equal(
output_12030[["l2"]],
c(8.53304762574407e-17, 1.2995814250075e-24, 3.44247710846988e-14,
7.86200945932739e-24, 3.39227019302602e-47, 0.99999999975886,
7.02248235171148e-19),
tolerance = 1e-10)
expect_equal(
output_12030[["l3"]],
c(1, 5.21584892208621e-20, 1.29958142500747e-24, 0.999999998312468,
1.60381089054864e-28, 1.02618796292273e-10, 1),
tolerance = 1e-10)
expect_equal(
output_12030[["c1"]],
structure(1:7, .Label = c("a", "b", "c", "d", "e", "f", "g"),
class = "factor"))
# Testing column names
expect_equal(
names(output_12030),
c("l1", "l2", "l3", "c1"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_12030),
c("numeric", "numeric", "numeric", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_12030),
c("double", "double", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_12030),
c(7L, 4L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_12030)),
character(0),
fixed = TRUE)
# Testing softmax(data = df, cols = 4, axis = "r")
# Testing side effects
expect_error(
xpectr::strip_msg(softmax(data = df, cols = 4, axis = "r")),
xpectr::strip("softmax() only works on numeric columns."),
fixed = TRUE)
# Testing softmax(data = df, cols = NA, axis = "r")
# Testing side effects
expect_error(
xpectr::strip_msg(softmax(data = df, cols = NA, axis = "r")),
xpectr::strip(paste0("Assertion on 'must.include' failed. Must be of class 'string",
"', not 'logical'.")),
fixed = TRUE)
# Testing softmax(data = df, cols = "l4", axis = "r")
# Testing side effects
expect_error(
xpectr::strip_msg(softmax(data = df, cols = "l4", axis = "r"), lowercase = TRUE),
xpectr::strip("Must include the elements {l4}.", lowercase = TRUE), # colnames(data)
fixed = TRUE)
# Testing softmax(data = df, cols = c("l1", "l2", "l3"),...
# Assigning output
output_16124 <- softmax(data = df, cols = c("l1", "l2", "l3"), axis = "c")
# Testing class
expect_equal(
class(output_16124),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
output_16124[["l1"]],
c(7.28100438257926e-33, 5.60257652385053e-09, 0.999960749299178,
9.60230314258677e-24, 1.67010452367847e-05, 1.33011953925298e-33,
2.25440530085991e-05),
tolerance = 1e-10)
expect_equal(
output_16124[["l2"]],
c(5.80920346814549e-23, 2.89223210231392e-24, 1.36740090845997e-05,
1.77704882117296e-29, 2.2504840460157e-43, 3.81432120430906e-15,
0.999986325990915),
tolerance = 1e-10)
expect_equal(
output_16124[["l3"]],
c(4.78089288388547e-25, 8.15175738259058e-38, 3.62514091914356e-34,
1.58731233695789e-24, 7.47197233734299e-43, 2.74878500791021e-43,
1),
tolerance = 1e-10)
expect_equal(
output_16124[["c1"]],
structure(1:7, .Label = c("a", "b", "c", "d", "e", "f", "g"),
class = "factor"))
# Testing column names
expect_equal(
names(output_16124),
c("l1", "l2", "l3", "c1"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_16124),
c("numeric", "numeric", "numeric", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_16124),
c("double", "double", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_16124),
c(7L, 4L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_16124)),
character(0),
fixed = TRUE)
# Testing softmax(data = df, cols = c("l1", "l2", "l3"),...
# Testing side effects
expect_error(
xpectr::strip_msg(softmax(data = df, cols = c("l1", "l2", "l3"), axis = "x")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'axis': Must be element of",
" set {'r','c'}, but is 'x'.")),
fixed = TRUE)
# Testing softmax(data = df, cols = c("l1", "l2", "l3"),...
# Testing side effects
expect_error(
xpectr::strip_msg(softmax(data = df, cols = c("l1", "l2", "l3"), axis = NA)),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'axis': Must be element of",
" set {'r','c'}, but is 'NA'.")),
fixed = TRUE)
# Testing softmax(data = df, cols = c("l1", "l2", "l3"),...
# Testing side effects
expect_error(
xpectr::strip_msg(softmax(data = df, cols = c("l1", "l2", "l3"), axis = NULL)),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'axis': Must be a subset o",
"f {'r','c'}, not 'NULL'.")),
fixed = TRUE)
# Testing softmax(data = df, cols = NULL, axis = "r")
# Testing side effects
expect_error(
xpectr::strip_msg(softmax(data = df, cols = NULL, axis = "r")),
xpectr::strip("softmax() only works on numeric columns."),
fixed = TRUE)
# Testing softmax(data = NULL, cols = c("l1", "l2", "l3"...
# Testing side effects
expect_error(
xpectr::strip_msg(softmax(data = NULL, cols = c("l1", "l2", "l3"), axis = "r")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'data': Must be of type 'd",
"ata.frame', not 'NULL'.")),
fixed = TRUE)
# Testing softmax(data = df, cols = c("l1", "l2", "l3"),...
# Assigning output
output_19032 <- softmax(data = df, cols = c("l1", "l2", "l3"), axis = "r")
# Testing class
expect_equal(
class(output_19032),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
output_19032[["l1"]],
c(4.24835425529159e-18, 1, 0.999999999999972, 1.68752985466077e-09,
1, 1.38520885997973e-10, 6.28883849646162e-15),
tolerance = 1e-10)
expect_equal(
output_19032[["l2"]],
c(8.53304762574407e-17, 1.2995814250075e-24, 3.44247710846988e-14,
7.86200945932739e-24, 3.39227019302602e-47, 0.99999999975886,
7.02248235171148e-19),
tolerance = 1e-10)
expect_equal(
output_19032[["l3"]],
c(1, 5.21584892208621e-20, 1.29958142500747e-24, 0.999999998312468,
1.60381089054864e-28, 1.02618796292273e-10, 1),
tolerance = 1e-10)
expect_equal(
output_19032[["c1"]],
structure(1:7, .Label = c("a", "b", "c", "d", "e", "f", "g"),
class = "factor"))
# Testing column names
expect_equal(
names(output_19032),
c("l1", "l2", "l3", "c1"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_19032),
c("numeric", "numeric", "numeric", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_19032),
c("double", "double", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_19032),
c(7L, 4L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_19032)),
character(0),
fixed = TRUE)
## Finished testing 'softmax' ####
})
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library(cvms)
context("softmax()")
test_that("softmax_vector() works", {
logits <- c(2, 57, 76, 23, 65, 0.3, 65.3)
exp_logits <- exp(logits)
sum_exp_logits <- sum(exp_logits)
softmaxed <- exp_logits/sum_exp_logits
expect_equal(softmax_vector(logits), softmaxed)
expect_equal(softmax_vector(2, 57, 76, 23, 65, 0.3, 65.3), softmaxed)
expect_equal(sum(softmax_vector(logits)), 1)
expect_equal(sum(softmax_vector(-logits)), 1)
## Testing 'softmax_vector(logits)' ####
## Initially generated by xpectr
# Assigning output
output_12505 <- softmax_vector(logits)
# Testing class
expect_equal(
class(output_12505),
"numeric",
fixed = TRUE)
# Testing type
expect_type(
output_12505,
type = "double")
# Testing values
expect_equal(
output_12505,
c(7.28100438257926e-33, 5.60257652385053e-09, 0.999960749299178,
9.60230314258677e-24, 1.67010452367847e-05, 1.33011953925298e-33,
2.25440530085991e-05),
tolerance = 1e-4)
# Testing names
expect_equal(
names(output_12505),
NULL,
fixed = TRUE)
# Testing length
expect_equal(
length(output_12505),
7L)
# Testing sum of element lengths
expect_equal(
sum(xpectr::element_lengths(output_12505)),
7L)
## Finished testing 'softmax_vector(logits)' ####
})
test_that("softmax() works", {
df <- data.frame(
"l1" = c(2, 57, 76, 23, 65, 0.3, 65.3),
"l2" = c(5, 2, 45,-10,-42, 23, 56.2),
"l3" = c(42, 12.6, 21, 43.2, 1, 0, 98),
"c1" = factor(c("a", "b", "c", "d", "e", "f", "g"),
levels = c("a", "b", "c", "d", "e", "f", "g"))
)
vector_softmax <- function(...){
exp_logits <- exp(c(...))
sum_exp_logits <- sum(exp_logits)
exp_logits/sum_exp_logits
}
df_colwise_softmaxed <- df %>%
dplyr::mutate(l1 = vector_softmax(l1),
l2 = vector_softmax(l2),
l3 = vector_softmax(l3))
expect_equal(as.data.frame(softmax(df, cols = c("l1", "l2", "l3"), axis = "c"), stringsAsFactors=TRUE),
as.data.frame(df_colwise_softmaxed), stringsAsFactors=TRUE)
df_rowwise_softmaxed <- plyr::ldply(seq_len(nrow(df)), function(r){
vector_softmax(unlist(df[r,c("l1","l2","l3")], recursive = TRUE, use.names = TRUE))
}) %>% dplyr::as_tibble() %>%
dplyr::mutate(c1 = df$c1)
expect_equal(as.data.frame(softmax(df, cols = c("l1", "l2", "l3"), axis = "r"), stringsAsFactors=TRUE),
as.data.frame(df_rowwise_softmaxed), stringsAsFactors=TRUE)
## Test with gxs_function
# xpectr::gxs_function(fn = softmax,
# args_values = list(
# "data" = list(df, NA, 1),
# "cols" = list(c("l1", "l2", "l3"),
# c(1, 2, 3),
# 4, NA, "l4"),
# "axis" = list("r", "c", "x", NA)
# ), indentation = 2,
# tolerance = "1e-10",
# round_to_tolerance = FALSE)
#
## Testing 'softmax' ####
## Initially generated by xpectr
# Testing different combinations of argument values
# Testing softmax(data = NA, cols = c("l1", "l2", "l3"),...
# Testing side effects
expect_error(
xpectr::strip_msg(softmax(data = NA, cols = c("l1", "l2", "l3"), axis = "r")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'data': Must be of type 'd",
"ata.frame', not 'logical'.")),
fixed = TRUE)
# Testing softmax(data = 1, cols = c("l1", "l2", "l3"), ...
# Testing side effects
expect_error(
xpectr::strip_msg(softmax(data = 1, cols = c("l1", "l2", "l3"), axis = "r")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'data': Must be of type 'd",
"ata.frame', not 'double'.")),
fixed = TRUE)
# Testing softmax(data = df, cols = c(1, 2, 3), axis = "r")
# Assigning output
output_12030 <- softmax(data = df, cols = c(1, 2, 3), axis = "r")
# Testing class
expect_equal(
class(output_12030),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
output_12030[["l1"]],
c(4.24835425529159e-18, 1, 0.999999999999972, 1.68752985466077e-09,
1, 1.38520885997973e-10, 6.28883849646162e-15),
tolerance = 1e-10)
expect_equal(
output_12030[["l2"]],
c(8.53304762574407e-17, 1.2995814250075e-24, 3.44247710846988e-14,
7.86200945932739e-24, 3.39227019302602e-47, 0.99999999975886,
7.02248235171148e-19),
tolerance = 1e-10)
expect_equal(
output_12030[["l3"]],
c(1, 5.21584892208621e-20, 1.29958142500747e-24, 0.999999998312468,
1.60381089054864e-28, 1.02618796292273e-10, 1),
tolerance = 1e-10)
expect_equal(
output_12030[["c1"]],
structure(1:7, .Label = c("a", "b", "c", "d", "e", "f", "g"),
class = "factor"))
# Testing column names
expect_equal(
names(output_12030),
c("l1", "l2", "l3", "c1"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_12030),
c("numeric", "numeric", "numeric", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_12030),
c("double", "double", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_12030),
c(7L, 4L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_12030)),
character(0),
fixed = TRUE)
# Testing softmax(data = df, cols = 4, axis = "r")
# Testing side effects
expect_error(
xpectr::strip_msg(softmax(data = df, cols = 4, axis = "r")),
xpectr::strip("softmax() only works on numeric columns."),
fixed = TRUE)
# Testing softmax(data = df, cols = NA, axis = "r")
# Testing side effects
expect_error(
xpectr::strip_msg(softmax(data = df, cols = NA, axis = "r")),
xpectr::strip(paste0("Assertion on 'must.include' failed. Must be of class 'string",
"', not 'logical'.")),
fixed = TRUE)
# Testing softmax(data = df, cols = "l4", axis = "r")
# Testing side effects
expect_error(
xpectr::strip_msg(softmax(data = df, cols = "l4", axis = "r"), lowercase = TRUE),
xpectr::strip("Must include the elements {l4}.", lowercase = TRUE), # colnames(data)
fixed = TRUE)
# Testing softmax(data = df, cols = c("l1", "l2", "l3"),...
# Assigning output
output_16124 <- softmax(data = df, cols = c("l1", "l2", "l3"), axis = "c")
# Testing class
expect_equal(
class(output_16124),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
output_16124[["l1"]],
c(7.28100438257926e-33, 5.60257652385053e-09, 0.999960749299178,
9.60230314258677e-24, 1.67010452367847e-05, 1.33011953925298e-33,
2.25440530085991e-05),
tolerance = 1e-10)
expect_equal(
output_16124[["l2"]],
c(5.80920346814549e-23, 2.89223210231392e-24, 1.36740090845997e-05,
1.77704882117296e-29, 2.2504840460157e-43, 3.81432120430906e-15,
0.999986325990915),
tolerance = 1e-10)
expect_equal(
output_16124[["l3"]],
c(4.78089288388547e-25, 8.15175738259058e-38, 3.62514091914356e-34,
1.58731233695789e-24, 7.47197233734299e-43, 2.74878500791021e-43,
1),
tolerance = 1e-10)
expect_equal(
output_16124[["c1"]],
structure(1:7, .Label = c("a", "b", "c", "d", "e", "f", "g"),
class = "factor"))
# Testing column names
expect_equal(
names(output_16124),
c("l1", "l2", "l3", "c1"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_16124),
c("numeric", "numeric", "numeric", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_16124),
c("double", "double", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_16124),
c(7L, 4L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_16124)),
character(0),
fixed = TRUE)
# Testing softmax(data = df, cols = c("l1", "l2", "l3"),...
# Testing side effects
expect_error(
xpectr::strip_msg(softmax(data = df, cols = c("l1", "l2", "l3"), axis = "x")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'axis': Must be element of",
" set {'r','c'}, but is 'x'.")),
fixed = TRUE)
# Testing softmax(data = df, cols = c("l1", "l2", "l3"),...
# Testing side effects
expect_error(
xpectr::strip_msg(softmax(data = df, cols = c("l1", "l2", "l3"), axis = NA)),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'axis': Must be element of",
" set {'r','c'}, but is 'NA'.")),
fixed = TRUE)
# Testing softmax(data = df, cols = c("l1", "l2", "l3"),...
# Testing side effects
expect_error(
xpectr::strip_msg(softmax(data = df, cols = c("l1", "l2", "l3"), axis = NULL)),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'axis': Must be a subset o",
"f {'r','c'}, not 'NULL'.")),
fixed = TRUE)
# Testing softmax(data = df, cols = NULL, axis = "r")
# Testing side effects
expect_error(
xpectr::strip_msg(softmax(data = df, cols = NULL, axis = "r")),
xpectr::strip("softmax() only works on numeric columns."),
fixed = TRUE)
# Testing softmax(data = NULL, cols = c("l1", "l2", "l3"...
# Testing side effects
expect_error(
xpectr::strip_msg(softmax(data = NULL, cols = c("l1", "l2", "l3"), axis = "r")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'data': Must be of type 'd",
"ata.frame', not 'NULL'.")),
fixed = TRUE)
# Testing softmax(data = df, cols = c("l1", "l2", "l3"),...
# Assigning output
output_19032 <- softmax(data = df, cols = c("l1", "l2", "l3"), axis = "r")
# Testing class
expect_equal(
class(output_19032),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
output_19032[["l1"]],
c(4.24835425529159e-18, 1, 0.999999999999972, 1.68752985466077e-09,
1, 1.38520885997973e-10, 6.28883849646162e-15),
tolerance = 1e-10)
expect_equal(
output_19032[["l2"]],
c(8.53304762574407e-17, 1.2995814250075e-24, 3.44247710846988e-14,
7.86200945932739e-24, 3.39227019302602e-47, 0.99999999975886,
7.02248235171148e-19),
tolerance = 1e-10)
expect_equal(
output_19032[["l3"]],
c(1, 5.21584892208621e-20, 1.29958142500747e-24, 0.999999998312468,
1.60381089054864e-28, 1.02618796292273e-10, 1),
tolerance = 1e-10)
expect_equal(
output_19032[["c1"]],
structure(1:7, .Label = c("a", "b", "c", "d", "e", "f", "g"),
class = "factor"))
# Testing column names
expect_equal(
names(output_19032),
c("l1", "l2", "l3", "c1"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_19032),
c("numeric", "numeric", "numeric", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_19032),
c("double", "double", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_19032),
c(7L, 4L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_19032)),
character(0),
fixed = TRUE)
## Finished testing 'softmax' ####
})
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